Teleworking behavior pre-, during, and expected post-COVID: Identification and empirical description of trajectory types

Abstract

Teleworking is a major lifestyle change whose adoption expanded substantially during the COVID-19 pandemic, and which might permanently change the working habits of some. To understand how much during-COVID teleworking behavior will “stick” in the post-pandemic world, this study explores pre-, during-, and expected post-COVID teleworking frequency trajectories based on during-COVID survey responses, which were weighted to represent the population shares of non–/non-usual/usual teleworkers (TWers). Taking respondents’ self-reported expectations at face value, post-COVID teleworking frequency will be 2.6–3.3 times that of pre-COVID, but we suspect that those expectations are over-optimistic. We developed a typology based on the teleworking trajectories, and identified eight mutually exclusive and collectively exhaustive worker segments: Climbers (13.6%), Plateauers (8.4%), Cappers (12.6%), Stable unables (43.1%), Stable non-choosers (13.5%), Stable non-usual TWers (1.5%), Stable usual TWers (3.2%), and Reducers (4.0%). We conducted three exploratory factor analyses and identified latent attitudinal constructs including 11 general, 7 work-related, and 7 telework-related attitudes. We profiled the eight segments regarding various attitudes and sociodemographic traits to reveal their potential connections to teleworking behavior, and to suggest further explorations with respect to residential location, vehicle ownership, and other travel patterns. Specifically, we see research needs pertaining to residential relocation and household vehicle ownership changes for segments expecting net increases in teleworking frequency between pre- and post-COVID. We also observed heterogeneity of teleworking adoption/frequency choices, attitudes, and travel behaviors among (tele)worker segments. Overall, this study deepens our understanding of post-COVID teleworking behavior changes, and provides a starting point for understanding the heterogeneity among (tele)workers. © 2023 The Author(s)